IMPACT: Impersonation attack detection via edge computing using deep autoencoder and feature abstraction

An ever-increasing number of computing devices interconnected through wireless networks encapsulated in the cyber-physical-social systems and a significant amount of sensitive network data transmitted among them have raised security and privacy concerns. Intrusion detection system (IDS) is known as an effective defence mechanism and most recently machine learning (ML) methods are used for its development. However, Internet of Things (IoT) devices often have limited computational resources such as limited energy source, computational power and memory, thus, traditional ML-based IDS that require extensive computational resources are not suitable for running on such devices. This study thus is to design and develop a lightweight ML-based IDS tailored for the resource-constrained devices. Specifically, the study proposes a lightweight ML-based IDS model namely IMPACT (IMPersonation Attack deteCTion using deep auto-encoder and feature abstraction). This is based on deep feature learning with gradient-based linear Support Vector Machine (SVM) to deploy and run on resource-constrained devices by reducing the number of features through feature extraction and selection using a stacked autoencoder (SAE), mutual information (MI) and C4.8 wrapper. The IMPACT is trained on Aegean Wi-Fi Intrusion Dataset (AWID) to detect impersonation attack. Numerical results show that the proposed IMPACT achieved 98.22% accuracy with 97.64% detection rate and 1.20% false alarm rate and outperformed existing state-of-the-art benchmark models. Another key contribution of this study is the investigation of the features in AWID dataset for its usability for further development of IDS

Experimental demonstration of machine-learning-aided QoT estimation in multi-domain elastic optical networks with alien wavelengths

In multi-domain elastic optical networks with alien wavelengths, each domain needs to consider intradomain and interdomain alien traffic to estimate and guarantee the required quality of transmission (QoT) for each lightpath and perform provisioning operations. This paper experimentally demonstrates an alien wavelength performance monitoring technique and machine-learning-aided QoT estimation for lightpath provisioning of intradomain/interdomain traffic. Testbed experiments demonstrate modulation format recognition, QoT monitoring, and cognitive routing for a 160 Gbaud alien multi-wavelength lightpath. By using experimental training datasets from the testbed and an artificial neural network, we demonstrated an accurate optical-signal-to-noise ratio prediction with an accuracy of ~95% when using 1200 data points.Peer ReviewedPostprint (author's final draft

Differential cartilaginous tissue formation by human synovial membrane, fat pad, meniscus cells and articular chondrocytes

Objective: To identify an appropriate cell source for the generation of meniscus substitutes, among those which would be available by arthroscopy of injured knee joints. Methods: Human inner meniscus cells, fat pad cells (FPC), synovial membrane cells (SMC) and articular chondrocytes (AC) were expanded with or without specific growth factors (Transforming growth factor-betal, Fibroblast growth factor-2 and Plate let-derived growth factor bb, TFP) and then induced to form three-dimensional cartilaginous tissues in pellet cultures, or using a hyaluronan-based scaffold (Hyaff(R)-11), in culture or in nude mice. Human native menisci were assessed as reference. Results: Cell expansion with TFP enhanced glycosaminoglycan (GAG) deposition by all cell types (up to 4.1-fold) and messenger RNA expression of collagen type II by FPC and SMC (up to 472-fold) following pellet culture. In all models, tissues generated by AC contained the highest fractions of GAG (up to 1.9 were positively stained for collagen type II (specific of the inner avascular region of meniscus), type IV (mainly present in the outer vascularized region of meniscus) and types I, III and VI (common to both meniscus regions). Instead, inner meniscus, FPC and SMC developed tissues containing negligible GAG and no detectable collagen type II protein. Tissues generated by AC remained biochemically and phenotypically stable upon ectopic implantation. Conclusions: Under our experimental conditions, only AC generated tissues containing relevant amounts of GAG and with cell phenotypes compatible with those of the inner and outer meniscus regions. Instead, the other investigated cell sources formed tissues resembling only the outer region of meniscus. It remains to be determined whether grafts based on AC will have the ability to reach the complex structural and functional organization typical of meniscus tissue. (C) 2006 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights rese

A Method for Assaying Deubiquitinating Enzymes

A general method for the assay of deubiquitinating enzymes was described in detail using (125)I-labeled ubiquitin-fused αNH-MHISPPEPESEEEEEHYC (referred to as Ub-PESTc) as a substrate. Since the tyrosine residue in the PESTc portion of the fusion protein was almost exclusively radioiodinated under a mild labeling condition, such as using IODO-BEADS, the enzymes could be assayed directly by simple measurement of the radioactivity released into acid soluble products. Using this assay protocol, we could purify six deubiquitinating enzymes from chick skeletal muscle and yeast and compare their specific activities. Since the extracts of E. coli showed little or no activity against the substrate, the assay protocol should be useful for identification and purification of eukaryotic deubiquitinating enzymes cloned and expressed in the cells

Abnormal Myocardial Contractility After Pediatric Heart Transplantation by Cardiac MRI

Cardiolog

Using Datamining Techniques to Help Metaheuristics: A Short Survey

International audienceHybridizing metaheuristic approaches becomes a common way to improve the efficiency of optimization methods. Many hybridizations deal with the combination of several optimization methods. In this paper we are interested in another type of hybridization, where datamining approaches are combined within an optimization process. Hence, we propose to study the interest of combining metaheuristics and datamining through a short survey that enumerates the different opportunities of such combinations based on literature examples

Microlensing as a probe of the Galactic structure; 20 years of microlensing optical depth studies

Microlensing is now a very popular observational astronomical technique. The investigations accessible through this effect range from the dark matter problem to the search for extra-solar planets. In this review, the techniques to search for microlensing effects and to determine optical depths through the monitoring of large samples of stars will be described. The consequences of the published results on the knowledge of the Milky-Way structure and its dark matter component will be discussed. The difficulties and limitations of the ongoing programs and the perspectives of the microlensing optical depth technique as a probe of the Galaxy structure will also be detailed.Comment: Accepted for publication in General Relativity and Gravitation. General Relativity and Gravitation in press (2010) 0

The effect of inhomogeneities on the distance to the last scattering surface and the accuracy of the CMB analysis

The standard analysis of the CMB data assumes that the distance to the last scattering surface can be calculated using the distance-redshift relation as in the Friedmann model. However, in the inhomogeneous universe, even if =0, the distance relation is not the same as in the unperturbed universe. This can be of serious consequences as a change of distance affects the mapping of CMB temperature fluctuations into the angular power spectrum. In addition, if the change of distance is relatively uniform no new temperature fluctuations are generated. It is therefore a different effect than the lensing or ISW effects which introduce additional CMB anisotropies. This paper shows that the accuracy of the CMB analysis can be impaired by the accuracy of calculation of the distance within the cosmological models. Since this effect has not been fully explored before, to test how the inhomogeneities affect the distance-redshift relation, several methods are examined: the Dyer-Roeder relation, lensing approximation, and non-linear Swiss-Cheese model. In all cases, the distance to the last scattering surface is different than when homogeneity is assumed. The difference can be as low as 1% and as high as 80%. Excluding extreme cases, the distance changes by about 20-30%. Since the distance to the last scattering surface is set by the position of the CMB peaks, in order to have a good fit, the distance needs to be adjusted. After correcting the distance, the cosmological parameters change. Therefore, a not properly estimated distance to the last scattering surface can be a major source of systematics. This paper shows that if inhomogeneities are taken into account when calculating the distance then models with positive spatial curvature and with \Omega_\Lambda ~ 0.8-0.9 are preferred. The \Lambda CDM model in most cases, is at odds with the current data.Comment: 18 pages, 6 figure

Measurement of the p-pbar -> Wgamma + X cross section at sqrt(s) = 1.96 TeV and WWgamma anomalous coupling limits

The WWgamma triple gauge boson coupling parameters are studied using p-pbar -> l nu gamma + X (l = e,mu) events at sqrt(s) = 1.96 TeV. The data were collected with the DO detector from an integrated luminosity of 162 pb^{-1} delivered by the Fermilab Tevatron Collider. The cross section times branching fraction for p-pbar -> W(gamma) + X -> l nu gamma + X with E_T^{gamma} > 8 GeV and Delta R_{l gamma} > 0.7 is 14.8 +/- 1.6 (stat) +/- 1.0 (syst) +/- 1.0 (lum) pb. The one-dimensional 95% confidence level limits on anomalous couplings are -0.88 < Delta kappa_{gamma} < 0.96 and -0.20 < lambda_{gamma} < 0.20.Comment: Submitted to Phys. Rev. D Rapid Communication